2016-12-09T15:31:23ZAlternatives using the Leap Motion to extend mid-air word-gesture keyboards.http://hdl.handle.net/2104/9660
Alternatives using the Leap Motion to extend mid-air word-gesture keyboards.
Lately, the use of touchless, mid-air, gesture-based interactions has increased significantly due to the popularity of augmented and virtual reality and advances in other industries (e.g., medicine, gaming), and with this wide-spread application comes the need for effecient, mid-air text-entry. Word-gesture keyboards have garnered attention in recent years, now coming standard on most Android devices, offering efficient means of gesture-based text-entry. For the first time, Markussen et al. combined the two with the inception of Vulture \cite{ref_vulture}, the first mid-air, word-gesture keyboard, providing the fastest means of mid-air text-entry yet. This thesis builds on the findings of Markussen et al. and presents alternatives means for word separation in mid-air text-entry for word-gesture keyboards, exploring and identifying the problems of new techniques and presenting possible solutions. Of the new techniques, a bimodal approach shows great promise, reaching a mean text-entry rate of 15.8 Words Per Minutes for a single session with no training.
2015-12-14T00:00:00ZModels for rested touchless gestural interaction.http://hdl.handle.net/2104/9463
Models for rested touchless gestural interaction.
Touchless mid-air gestural interaction has gained mainstream attention with the emergence of off-the-shelf commodity devices such as the Leap Motion and the Xbox Kinect. One of the issues with this form of interaction is fatigue, a problem colloquially known as the "Gorilla Arm Syndrome.'' However, by allowing interaction from a rested position, whereby the elbow is rested on a surface, this problem can be limited in its effect. In this paper we evaluate 3 possible methods for performing touchless mid-air gestural interaction from a rested position: a basic rested interaction, a simple calibrated interaction which models palm positions onto a hyperplane, and a more complex calibration which models the arm's interaction space using the angles of the forearm as input. The results of this work found that the two modeled interactions conform to Fitts's law and also demonstrated that implementing a simple model can improve interaction by improving performance and accuracy.
2015-07-31T00:00:00ZGiving the users a hand : towards touchless hand gestures for the desktop.http://hdl.handle.net/2104/9157
Giving the users a hand : towards touchless hand gestures for the desktop.
Hari Haran, Alvin Jude.
Touchless, mid-air, gesture-based interactions have recently moved out of laboratories and Hollywood movies and into the hands of users. There is little difference in the interaction style and techniques used today from that of the 1980's, despite advances in the technology enabling this interaction. For this interaction to achieve mainstream popularity, and to be as ubiquitous as the keyboard or the mouse, common problems such as the "Gorilla Arm Syndrome'' will have to be addressed. Additionally, the common use-case such as gestural navigation, selection, and manipulation will need to be improved and eventually standardized. This thesis presents solutions to existing problems and introduces possible interaction techniques that allows users to perform the actions above. This is expected to pave the way for touchless mid-air hand gestures to be a ubiquitous form of interaction on the desktop.
2014-09-05T00:00:00ZFaster k-means clustering.http://hdl.handle.net/2104/8826
Faster k-means clustering.
Drake, Jonathan, 1989-
The popular k-means algorithm is used to discover clusters in vector data automatically. We present three accelerated algorithms that compute exactly the same clusters much faster than the standard method. First, we redesign Hamerly’s algorithm to use k heaps to avoid checking distance bounds for all n points, with little empirical gain. Second, we use an adaptive number of distance bounds to avoid redundant calculations (Drake and Hamerly 2012). Experiments show the superior performance of adaptive k-means in medium dimension (20 ≤ d ≤ 200) on uniform random data. Finally, we reformulate the triangle inequality to constrain the search space for a point’s nearest center to an annular region centered at the origin. For uniform random data, annulus k-means is competitive with or much faster than other algorithms in low dimension (d < 20), and it outperforms other algorithms on five of six naturally-clustered, real-world datasets tested (d ≤ 74).
2013-09-24T00:00:00Z